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Fees
₹3,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹3,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
180
Students
1,200
Seats
180
Students
1,200
The Electrical Engineering program at Major S D Singh University Farrukhabad is structured over eight semesters, ensuring a progressive learning journey from foundational sciences to advanced engineering concepts. The curriculum balances theoretical knowledge with practical application through laboratory sessions, mini-projects, and a final-year capstone project.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | MTH101 | Calculus I | 3-0-0-3 | - |
| 1 | PHY101 | Physics I | 3-0-0-3 | - |
| 1 | CHM101 | Chemistry I | 3-0-0-3 | - |
| 1 | ENG101 | English Communication | 2-0-0-2 | - |
| 1 | CSE101 | Introduction to Programming | 2-0-2-3 | - |
| 1 | EE101 | Basic Electrical Engineering | 3-0-0-3 | - |
| 1 | L101 | Electrical Lab I | 0-0-2-1 | - |
| 2 | MTH102 | Calculus II | 3-0-0-3 | MTH101 |
| 2 | PHY102 | Physics II | 3-0-0-3 | PHY101 |
| 2 | CHM102 | Chemistry II | 3-0-0-3 | CHM101 |
| 2 | CSE102 | Data Structures and Algorithms | 3-0-0-3 | CSE101 |
| 2 | EE102 | Electrical Circuits | 3-0-0-3 | EE101 |
| 2 | L102 | Electrical Lab II | 0-0-2-1 | L101 |
| 3 | MTH201 | Differential Equations | 3-0-0-3 | MTH102 |
| 3 | PHY201 | Electromagnetic Fields | 3-0-0-3 | PHY102 |
| 3 | EE201 | Signals and Systems | 3-0-0-3 | EE102 |
| 3 | EE202 | Network Analysis | 3-0-0-3 | EE102 |
| 3 | L201 | Electronics Lab I | 0-0-2-1 | L102 |
| 4 | MTH202 | Probability and Statistics | 3-0-0-3 | MTH201 |
| 4 | EE203 | Electromagnetic Waves | 3-0-0-3 | PHY201 |
| 4 | EE204 | Control Systems | 3-0-0-3 | EE201 |
| 4 | EE205 | Power Electronics | 3-0-0-3 | EE201 |
| 4 | L202 | Electronics Lab II | 0-0-2-1 | L201 |
| 5 | EE301 | Digital Signal Processing | 3-0-0-3 | EE201 |
| 5 | EE302 | Communication Systems | 3-0-0-3 | EE201 |
| 5 | EE303 | Microprocessors and Microcontrollers | 3-0-0-3 | EE204 |
| 5 | EE304 | Embedded Systems | 3-0-0-3 | EE303 |
| 5 | L301 | Control Systems Lab | 0-0-2-1 | L202 |
| 6 | EE305 | Power System Analysis | 3-0-0-3 | EE205 |
| 6 | EE306 | Renewable Energy Systems | 3-0-0-3 | EE301 |
| 6 | EE307 | VLSI Design | 3-0-0-3 | EE205 |
| 6 | EE308 | Artificial Intelligence | 3-0-0-3 | EE301 |
| 6 | L302 | Power Electronics Lab | 0-0-2-1 | L301 |
| 7 | EE401 | Capstone Project I | 0-0-6-6 | EE305 |
| 7 | EE402 | Special Topics in Electrical Engineering | 3-0-0-3 | - |
| 7 | EE403 | Advanced Embedded Systems | 3-0-0-3 | EE304 |
| 7 | EE404 | Research Methodology | 2-0-0-2 | - |
| 7 | L401 | Advanced Lab | 0-0-2-1 | L302 |
| 8 | EE405 | Capstone Project II | 0-0-6-6 | EE401 |
| 8 | EE406 | Elective I | 3-0-0-3 | - |
| 8 | EE407 | Elective II | 3-0-0-3 | - |
| 8 | EE408 | Elective III | 3-0-0-3 | - |
| 8 | L402 | Final Year Lab | 0-0-2-1 | L401 |
The advanced departmental electives offered in the Electrical Engineering program at Major S D Singh University Farrukhabad are designed to deepen students' understanding of specialized areas within the field. Each course is carefully curated to reflect current industry trends and emerging technologies.
Digital Signal Processing: This course explores mathematical foundations, filter design techniques, and modern DSP algorithms used in audio processing, image analysis, and telecommunications. Students learn to implement these concepts using MATLAB and Python frameworks.
Communication Systems: Focuses on analog and digital modulation schemes, noise analysis, and error correction codes. The course includes hands-on labs where students simulate communication channels and evaluate performance metrics.
Microprocessors and Microcontrollers: Introduces architecture, programming, and interfacing of microprocessor-based systems. Students gain practical experience in developing embedded applications using ARM Cortex-M series processors.
Embedded Systems: Covers design principles, real-time operating systems, and hardware-software co-design. The curriculum emphasizes development tools like Keil, IAR Embedded Workbench, and Linux-based embedded platforms.
Power System Analysis: Examines steady-state and transient behavior of power systems under normal and fault conditions. Includes modeling techniques, stability analysis, and protection schemes for large-scale networks.
Renewable Energy Systems: Explores solar photovoltaics, wind turbines, hydroelectric plants, and battery storage technologies. Students analyze system efficiency, cost-benefit models, and integration strategies into existing grids.
VLSI Design: Delves into logic synthesis, circuit design automation, and layout implementation for integrated circuits. Labs involve using EDA tools like Cadence and Synopsys for designing custom chips.
Artificial Intelligence: Integrates machine learning models with electrical engineering applications. Topics include neural networks, deep learning architectures, reinforcement learning, and computer vision in embedded systems.
Control Systems: Builds upon foundational knowledge to study feedback control design, stability analysis, and optimal control theory. Students work on simulation-based projects involving robotic systems and industrial automation.
Power Electronics: Examines semiconductor devices, converters, inverters, and motor drives. The course combines theoretical understanding with practical lab experiments using IGBTs, MOSFETs, and thyristors.
Our department strongly believes in project-based learning as a means to bridge the gap between theory and practice. Projects are assigned at multiple levels throughout the program, beginning with guided mini-projects in early semesters and culminating in complex, industry-aligned capstone projects in the final year.
Mini-projects typically last 4-6 weeks and involve small teams working under faculty guidance. These projects focus on applying fundamental concepts to solve real-world problems. For instance, students might design a simple DC motor controller or build an analog filter circuit for audio processing.
The final-year capstone project spans several months and requires students to undertake an independent research endeavor. Students select their topics in consultation with faculty mentors based on their interests and career goals. The project involves literature review, experimental design, data collection, analysis, and documentation.
Faculty members play a crucial role as mentors, providing academic support, technical guidance, and industry insights throughout the project lifecycle. Regular progress reviews ensure that students stay on track and receive timely feedback for improvement.
